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Are Red Cell Indices a Reliable Screening Tool in Pre-Natal Screening for the Avoidance of E-Beta Thalassemia and Beta Thalassemia Major Births? Results of a Population Survey From Eastern India

2011· article· en· W2537755821 on OpenAlexaff
Shyamali Dutta, Tuphan Kanti Dolai, Rajat Kumar, Maitreyee Bhattacharyya, Barnali Chakraborti, Sharmistha Sanyal, Swarupa Bhattacharjee, Basab Bagchi, Rajib De, Malay Ghosh

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsMedicineThalassemiaBeta thalassemiaPopulationPediatricsDiseaseEnvironmental healthDemographyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Abstract 5303 The state of West Bengal in the eastern part of India has a high prevalence of the carrier states of beta thalassemia and Hb E. Analysis of Hb HPLC screening data from 200 individuals, including adults and children from urban areas around Kolkata in West Bengal, carried out in our institution1, reveals a prevalence 6.5% for beta trait and 5.5% for HbE trait. (unpublished data) It may be possible to reduce births of beta thalassemia major and E beta thalassemia by preventive strategies, including mass screening and awareness campaigns. The best preventive method is debatable, because of the highly variable prevalence of the haemoglobin disorders within defined geographic regions (Weatherall DJ, Blood.2010), the economic factors involved and most importantly the question of acceptance of prevention methods. Because of the social stigma attached to the diagnosis of a genetic disease, families of young men and women diagnosed as thalassemia carriers in community screening programs often suppress this information when marriages are arranged, according to prevalent social practice. Therefore pre-marital screening, in our experience, is unlikely to be effective in reducing the number of beta thalassemia major and E-Beta thalassemia births in eastern India. Antenatal screening on the other hand has the potential for greater acceptability. Concern for the welfare of the unborn child are likely to make prospective parents more amenable to counselling and getting themselves tested for the thalassemia carrier state. We analysed data of 1000 antenatal mothers (Table 1), who had undergone screening for the thalassemia carrier state by red cell indices and Hb HPLC, as part of a government funded screening programme conducted in our institution1 in Kolkata city of West Bengal, India, in order to determine whether red cell indices, which is more economical than Hb HPLC, was an effective screening tool. Results of Hb HPLC screening data of 1000 antenatal women (Table 1) Result Beta Trait (HbA2% 3.6-6.6) Hb E trait (A2+E% 22.8-42.8) E Beta E Disease Sickle trait Sickle Beta D Trait D disease No of cases (%) 58(5.8%) 48(4.8%) 3(0.2%) 2(0.2%) 2(0.2%) 1(0.1%) 1 1 Where both partners were carriers, mutations were confirmed by complementary reverse dot blot hybridisation or DNA sequencing. Red Cell Indices in Thalassemia Carrier States (Table 2) Thalassemia Carrier State (1000 Antenatal Women) MCV (fl) MCH (pg) Mean Range (±95%CI) (±2SD) Mean Range (±95%CI) (±2SD) Beta Trait (n= 58) 68.6±1.70 55.4–81.8 21.80±0.64 16.6–26.8 E Trait(n=48) 78.8±1.42 67.8–89.8 26.4±0.62 22.0–30.8 Most antenatal women received iron and folic acid supplements, therefore iron status was not separately examined. To exclude the possibility of the effect of pregnancy on red cell indices, evaluation of MCV and MCH in 50 HbE trait individuals and 250 beta trait drawn from community screening data, comprising non-pregnant females and males, with normal serum ferritin values, mean MCV was 76.6fl (range 66.3–86.8fl), mean MCH 25.6pg (range 21.5–29.7pg) for E trait. For beta trait mean MCV was 67.0 fl (range 50–84 fl), mean MCH 21 pg (range 15–26 pg). There was no statistically significant difference from antenatal cases (Student's t-test ). MCV of <80fl and MCH < 27pg were previously reported to predict most beta thalassemia in pregnancy (Weatherall and Clegg Eds, The Thalassemia Syndromes, Part 4. UK: Blackwell Science Ltd, 2001 ). We tested whether these values could reliably predict beta trait and E trait taken together, in 1000 antenatal women in the present study (Table 3) Red Cell Indices as Predictor of Beta Trait and HbE Trait (Table 3) Sensitivity (%) Specificity (%) Positive Predictive Value (%) Negative Predictive Value (%) No of Beta Trait Missed on Screening (%) n=58 No of E Trait Missed on Screening (%) n=48 MCV <80fl 88 85 42 98 6 (10.3) 15 (31.3) MCH <27pg 84 82 35.2 98 9 (15.5) 17 (35.4) Conclusion –MCH and MCV tend to be higher in E trait compared to beta trait. We recommend that in high prevalence areas, Hb HPLC should be performed in all antenatal women irrespective of red cell indices, to avoid missing thalassemia carriers and facilities for genetic diagnosis and counselling be made available to couples at risk of beta thalessemia major and E beta thalessemia births. Disclosures: No relevant conflicts of interest to declare.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.246
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2011
Admission routes1
Has abstractyes

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